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https://github.com/sierkinhane/crnn_chinese_characters_rec
(CRNN) Chinese Characters Recognition.
https://github.com/sierkinhane/crnn_chinese_characters_rec
deep-learning ocr pytorch recognition
Last synced: 6 days ago
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(CRNN) Chinese Characters Recognition.
- Host: GitHub
- URL: https://github.com/sierkinhane/crnn_chinese_characters_rec
- Owner: Sierkinhane
- Created: 2018-09-26T10:26:32.000Z (over 6 years ago)
- Default Branch: stable
- Last Pushed: 2022-11-13T07:20:34.000Z (about 2 years ago)
- Last Synced: 2025-01-08T15:13:20.175Z (13 days ago)
- Topics: deep-learning, ocr, pytorch, recognition
- Language: Python
- Homepage:
- Size: 181 MB
- Stars: 1,836
- Watchers: 37
- Forks: 541
- Open Issues: 79
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
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README
# Characters Recognition
A Chinese characters recognition repository based on convolutional recurrent networks. (**Below please scan the QR code to join the wechat group.**)
## Performance
#### Recognize characters in pictures
## Dev Environments
1. WIN 10 or Ubuntu 16.04
2. **PyTorch 1.2.0 (may fix ctc loss)** with cuda 10.0 🔥
3. yaml
4. easydict
5. tensorboardX
### Data
#### Synthetic Chinese String Dataset
1. Download the [dataset](https://pan.baidu.com/s/1ufYbnZAZ1q0AlK7yZ08cvQ)
2. Edit **lib/config/360CC_config.yaml** DATA:ROOT to you image path
```angular2html
DATASET:
ROOT: 'to/your/images/path'
```
3. Download the [labels](https://pan.baidu.com/s/1oOKFDt7t0Wg6ew2uZUN9xg) (password: eaqb)
4. Put *char_std_5990.txt* in **lib/dataset/txt/**
5. And put *train.txt* and *test.txt* in **lib/dataset/txt/**
eg. test.txt
```
20456343_4045240981.jpg 89 201 241 178 19 94 19 22 26 656
20457281_3395886438.jpg 120 1061 2 376 78 249 272 272 120 1061
...
```
#### Or your own data
1. Edit **lib/config/OWN_config.yaml** DATA:ROOT to you image path
```angular2html
DATASET:
ROOT: 'to/your/images/path'
```
2. And put your *train_own.txt* and *test_own.txt* in **lib/dataset/txt/**
eg. test_own.txt
```
20456343_4045240981.jpg 你好啊！祖国！
20457281_3395886438.jpg 晚安啊！世界！
...
```
**note**: fixed-length training is supported. yet you can modify dataloader to support random length training.
## Train
```angular2html
[run] python train.py --cfg lib/config/360CC_config.yaml
or [run] python train.py --cfg lib/config/OWN_config.yaml
```
```
#### loss curve
```angular2html
[run] cd output/360CC/crnn/xxxx-xx-xx-xx-xx/
[run] tensorboard --logdir log
```
#### loss overview(first epoch)
## Demo
```angular2html
[run] python demo.py --image_path images/test.png --checkpoint output/checkpoints/mixed_second_finetune_acc_97P7.pth
```
## References
- https://github.com/meijieru/crnn.pytorch
- https://github.com/HRNet